Welcome to PECTEN

Market Radar

Our Product

What is Pecten

Pecten is a financial market radar powered by Artificial Intelligence that generates investment strategies for Asset Managers. 

Pecten is a robust Analytics Engine compared to traditional financial modelling that taps into the streams of "unstructured" data that global digitalization and social media are continuously creating. 

Pecten provides Predictive Analytics to generate investment ideas or as an early warning signal for assets at risk. 

Why choose us?

  

Behavioural economists suggest that investor perceptions affect markets in predictable ways. It is proven to be profitable to consider economic and market sentiments to make investment decisions.

Investors are receptive to incorporating non-traditional indicators into their trading models to gain an edge in the market.  Social and news data offer much stronger performance, when layered on top of traditional data sources.

Growth of data is steadily increasing, making it  hard to process for humans yet more attractive to produce innovative analytics such as sentiments to generate alpha.

Pecten offers a real time capability that provides intelligence to understand patterns as they emerge. These can be be incorporated in quantitative or qualitative decision making process. 

How we deliver

Pecten extracts and combines news, social media, blogs, technical, and fundamentals data to create a holistic picture of organisations and their stock performance in real-time. 

Pecten uses Supervised and Unsupervised Machine Learning algorithms to learn from historic data ,identify patterns, trends and apply it in real-time. 

Pecten constantly listens to news, views, opinions and events; runs them through Natural Language Processing and Machine Learning engines to separate “data” from the “noise”. Pecten combines it with fundamentals and technical data to generate powerful insights and signals to drive real time well calibrated investment strategies. 

Use cases

Trading Strategy using sentiment analysis

Constructing portfolios using sentiment indicators jointly with traditional factors can result in significant outperformance versus the benchmark.

The example on the left is the strategy’s back testing results of the portfolio which is constructed by using the Sentiment Indicators and 20-day momentum factor, together with other factors selected by Machine Learning.


The charts below show Pecten's Recommended Portfolio's performance comparing to DAX Benchmark.

Weekly Returns

Cumulative Returns

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